Currently, electronic documents are often converted from one type of document to another using the pre-converted electronic document's visual information. An Optical Character Recognition (OCR) process, for instance, scans a printed document or rasterizes an electronic copy of a document to gain this visual information. The OCR process then analyzes this visual information to determine the document's text, layout, and data-entry fields, which it uses to build an electronic document of another type.
But OCR and other current conversion processes are limited. They often build converted documents having static, limited functions. They often cannot effectively analyze electronic documents written in an unfamiliar human language. They often do not correctly recognize a document's data-entry fields. And they often do not inform a user about—or enable a user to fix—problems with the converted document.